1. Field of Invention
This invention relates to processes, apparatus, media and signals for automatically aligning objects in images, such as peaks in two-dimensional nuclear magnetic resonance spectra.
2. Description of Related Art
Object matching in images, also known as image alignment, has been an important topic in computer vision, object recognition, and image analysis. The performance of the matching method depends on the properties of the features and the matching measure used. One application where object matching in images can be performed is in the analysis of nuclear magnetic resonance (NMR) spectra and the alignment of equivalent peaks in such spectra to each other.
An NMR spectrum typically comprises a one-dimensional or multi-dimensional image that consists of objects that represent molecular features of a sample. Examples of molecular features of a sample include, but are not limited to, the presence of specific metabolites or other molecules within the sample. The use of NMR spectroscopy (NMR) for analyzing complex biological samples and comparing them to each other has a long history in medical applications. For example, comparative metabolic profiling of the endogenous metabolites produced by an individual (metabonomics) using NMR has been utilized in the early prediction of response to doxorubicin and interleukin-2 treatment. See, Ewens et al., 2006, Cancer Res. 66, 5419. Many metabonomics studies using NMR are based on one dimensional 1H NMR, which has less sample acquisition time and is easy to analyze. However, the high spectral congestion of 1H NMR spectra from complex biological samples limits the number of metabolites that can be uniquely identified and quantified.
Recently, two-dimensional 1H—13C NMR was used for analyzing global metabolic changes in the yeast metabolome. See, Peng, 2007, Metabolic Engineering 9, 8-20. Because almost all endogenous metabolites contain carbon, the second 13C NMR dimension provides a greatly extended spectral range (˜200 parts per million) and enables separation and accurate identification of many metabolites that congest into a single object along the 1H NMR dimension. However, comparing NMR metabolic profiles requires aligning NMR objects (peaks) representing the same metabolites across multiple spectra. The nature of 1H—13C NMR poses a couple of challenges. First, the position of an object representing the same metabolite across samples or replicates is not fixed in the two-dimensional 1H—13C NMR spectra. There is always slight position shifting observed because the experimental condition cannot be one hundred percent identical when each spectrum is measured: a slight difference in experimental conditions, such as pH, will cause an object to shift. Even for replicates from the same sample, such a shift is inevitable. Second, these shifts are not systematic. The direction and extent of the shift for each object is not consistent throughout a spectrum. The objects can shift towards different directions with different extent in the different areas of a spectrum. Furthermore, not all metabolites are present in all samples, so the capability to align an insignificant signal but not its neighboring significant signal to objects representing the same metabolite is desirable.
Thus, for the foregoing reasons, comparison of multidimensional NMR metabolic profiles presents a classic problem: the alignment of objects in images. In NMR, the objects are peaks that appear in the NMR spectra. Many images, such as NMR metabolic profiles, exhibit characteristics that can be exploited in order to align objects in the images. For example, although the object shifting of the NMR spectrum is globally inconsistent, the objects within a small region of the same spectrum display similar shifting patterns, in which such objects shift towards similar directions with similar extent. As a result, the local patterns across different spectra are usually matched. Conventional processes for aligning objects in images do not satisfactorily exploit these patterns of matched local shift. Accordingly, what are needed in the art are improved processes, apparatus, media and signals for aligning objects in a plurality images that take advantage of patterns of matched local shift.